中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
High-Resolution Land Cover Mapping Through Learning With Noise Correction

文献类型：期刊论文

作者Dong, Runmin1,2; Fang, Weizhen3; Fu, Haohuan1; Gan, Lin4; Wang, Jie5; Gong, Peng1
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2022
卷号60页码:13
关键词Noise measurement Training Task analysis Image resolution Satellites Noise robustness Image segmentation Deep learning high-resolution imagery noisy label semantic segmentation
ISSN号0196-2892
DOI10.1109/TGRS.2021.3068280
英文摘要High-resolution land cover mapping over large areas is a challenging task due to the lack of high-quality labels. A potential solution is to leverage the existing knowledge contained in the freely available lower-resolution land cover products. However, the relatively low resolution and low accuracy of the products lead to numerous inaccurate labels, which harms the performance of the neural network. This article addresses the challenge by jointly optimizing the network parameters and correcting the noisy labels with a novel online noise correction approach and a synergistic noise correction loss. By incorporating the information entropy as a measurement to determine the probable correct labels, the proposed noise correction approach learns to make effective correction of the noisy labels during training and eventually boosts the performance with a training set containing less noisy labels. Experimental results show that the proposed method can effectively correct the noisy labels and reduce their negative impact on network training. By employing the proposed method, we produce a refined high-resolution (3-m) land cover map from a lower-resolution (10-m) product in China and improve the accuracy from 74.96x0025; (10-m) to 81.32x0025; (3-m). Such an approach that can effectively learn from noisy data sets leads to many potential opportunities for using and magnifying existing knowledge and results.
资助项目National Key Research and Development Plan of China[2017YFA0604500] ; National Key Research and Development Plan of China[2017YFB0202204] ; National Key Research and Development Plan of China[2017YFA0604401] ; National Key Research and Development Plan of China[2020YFB0204700] ; National Natural Science Foundation of China[U1839206]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000730619400064
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/18391]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Fu, Haohuan; Gong, Peng
作者单位1.Tsinghua Univ, Dept Earth Syst Sci, Beijing 100084, Peoples R China
2.SenseTime Grp Ltd, Beijing 100084, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
4.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
5.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Dong, Runmin,Fang, Weizhen,Fu, Haohuan,et al. High-Resolution Land Cover Mapping Through Learning With Noise Correction[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:13.
APA Dong, Runmin,Fang, Weizhen,Fu, Haohuan,Gan, Lin,Wang, Jie,&Gong, Peng.(2022).High-Resolution Land Cover Mapping Through Learning With Noise Correction.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,13.
MLA Dong, Runmin,et al."High-Resolution Land Cover Mapping Through Learning With Noise Correction".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):13.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。